title: GBOOST: a GPU-based tool for detecting gene-gene interactions in genome-wide case control studies.
abstract: BACKGROUND
  Collecting millions of genetic variations is feasible with the advanced genotyping technology. With a huge amount of genetic variations data in hand, developing efficient algorithms to carry out the gene-gene interaction analysis in a timely manner has become one of the key problems in genome-wide association studies (GWAS). Boolean operation-based screening and testing (BOOST), a recent work in GWAS, completes gene-gene interaction analysis in 2.5 days on a desktop computer. Compared with central processing units (CPUs), graphic processing units (GPUs) are highly parallel hardware and provide massive computing resources. We are, therefore, motivated to use GPUs to further speed up the analysis of gene-gene interactions.
  
  
  RESULTS
  We implement the BOOST method based on a GPU framework and name it GBOOST. GBOOST achieves a 40-fold speedup compared with BOOST. It completes the analysis of Wellcome Trust Case Control Consortium Type 2 Diabetes (WTCCC T2D) genome data within 1.34 h on a desktop computer equipped with Nvidia GeForce GTX 285 display card.
  
  
  BACKGROUND
  GBOOST code is available at http://bioinformatics.ust.hk/BOOST.html#GBOOST.
authors.affiliation: Laboratory for Bioinformatics and Computational Biology, Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China. timyung@ust.hk
authors.forename: Ling Sing
authors.initials: LS
authors.lastname: Yung
authors.forename: Can
authors.initials: C
authors.lastname: Yang
authors.forename: Xiang
authors.initials: X
authors.lastname: Wan
authors.forename: Weichuan
authors.initials: W
authors.lastname: Yu
mesh_terms: D000465:Algorithms; D016022:Case-Control Studies; D019295:Computational Biology / Q000379:methods*; D003924:Diabetes Mellitus, Type 2 / Q000235:genetics; D055106:Genome-Wide Association Study; D023281:Genomics / Q000379:methods*; D006801:Humans; D020641:Polymorphism, Single Nucleotide; D012984:Software